AI is taking the healthcare industry by storm, and there are many important use cases for digital health companies, particularly in administrative and clinical decision support. But according to Omada Health, a virtual healthcare provider, there’s one purpose the company doesn’t use AI for. It’s about encouraging behavior change.
Omada is a virtual care company focused on behavior change for diabetes, weight management, hypertension, and musculoskeletal issues. However, he says that humans are more effective than AI in promoting behavior change. Carolyn Bradner Jusik, Chief Medical Officer Omada Health.
“Can anyone feel responsible for AI?” Jasik said in an interview. Viv Sunday in Los Angeles. “So if the AI tells the app user, ‘This is the trend we see in the data,’ or ‘Here’s what the situation looks like,’ the human patient will accept the automated suggestion and respond to it from a behavioral perspective. ? I think this is a very interesting question, especially now that AI has advanced so much. We still believe that humans want to be responsible to humans. ”
She added that when members communicate with Omada Health’s human coaches, they often ask if the coach is a bot because they want to work with a real person. Being guided by a real person gives patients more accountability and support, Jusik said.
That being said, AI is likely to evolve in the future.
“Perhaps in the future, AI will be able to feel empathetic and cooperative. But for now, we feel that humans still need to be in charge and have support.” ,” Jusik said.
What does Omada Health use AI for? Internally, we use this technology to streamline business operations and processes. This includes “part of the engineering workflow and staying on top of the latest clinical evidence,” Jusik said.
The company is also looking to incorporate AI into member care and enhance the work of healthcare providers through clinical decision support. This includes providing data and recommendations to help healthcare providers be more efficient and provide more personalized care. This is something she would have supported Jusik in the past, she said.
“When I was in clinical practice, one of the biggest challenges for patients with diabetes was figuring out how to match their treatment plan with what they were eating at home and their daily habits,” she says. Stated. “It takes a few minutes to look at their blood sugar data and food records, process it, and figure out what recommendations to make. AI is a great example of how it can do some of that work, but A human must be the last person to approve a recommendation before it is made.”
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